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Merge branch 'dev' of github.com:MaiM-with-u/MaiBot into dev

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This commit is contained in:
UnCLAS-Prommer
2025-09-13 11:11:44 +08:00
parent 27e4d2b803 3900684ffd
commit a196c940bf
8 changed files with 62 additions and 52 deletions
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32
src/chat/heart_flow/heartFC_chat.py
View File

@@ -199,7 +199,7 @@ class HeartFChatting:
# !处理no_reply_until_call逻辑
if self.no_reply_until_call:
for message in recent_messages_list:
if message.is_mentioned or message.is_at:
if message.is_mentioned or message.is_at or len(recent_messages_list) >= 8 or time.time() - self.last_read_time > 600:
self.no_reply_until_call = False
break
# 没有提到，继续保持沉默
@@ -333,6 +333,31 @@ class HeartFChatting:
loop_start_time=self.last_read_time,
available_actions=available_actions,
)
# !此处使at或者提及必定回复
metioned_message = None
for message in recent_messages_list:
if (message.is_mentioned or message.is_at) and global_config.chat.mentioned_bot_reply:
metioned_message = message
has_reply = False
for action in action_to_use_info:
if action.action_type == "reply":
has_reply =True
break
if not has_reply and metioned_message:
action_to_use_info.append(
ActionPlannerInfo(
action_type="reply",
reasoning="有人提到了你，进行回复",
action_data={},
action_message=metioned_message,
available_actions=available_actions,
)
)
# 3. 并行执行所有动作
action_tasks = [
@@ -350,18 +375,15 @@ class HeartFChatting:
reply_text_from_reply = ""
action_success = False
action_reply_text = ""
action_command = ""
for i, result in enumerate(results):
if isinstance(result, BaseException):
logger.error(f"{self.log_prefix} 动作执行异常: {result}")
continue
_cur_action = action_to_use_info[i]
if result["action_type"] != "reply":
action_success = result["success"]
action_reply_text = result["reply_text"]
action_command = result.get("command", "")
elif result["action_type"] == "reply":
if result["success"]:
reply_loop_info = result["loop_info"]
@@ -377,7 +399,6 @@ class HeartFChatting:
loop_info["loop_action_info"].update(
{
"action_taken": action_success,
"command": action_command,
"taken_time": time.time(),
}
)
@@ -391,7 +412,6 @@ class HeartFChatting:
"loop_action_info": {
"action_taken": action_success,
"reply_text": action_reply_text,
"command": action_command,
"taken_time": time.time(),
},
}

23
src/chat/planner_actions/planner.py
View File

@@ -39,6 +39,7 @@ def init_prompt():
"""
{time_block}
{name_block}
你的兴趣是：{interest}
{chat_context_description}，以下是具体的聊天内容
**聊天内容**
{chat_content_block}
@@ -60,6 +61,7 @@ reply
no_reply
动作描述：
保持沉默，不回复直到有新消息
控制聊天频率，不要太过频繁的发言
{{
"action": "no_reply",
}}
@@ -67,30 +69,18 @@ no_reply
no_reply_until_call
动作描述：
保持沉默，直到有人直接叫你的名字
当前话题不感兴趣时使用，或有人不喜欢你的发言时使用
{{
"action": "no_reply_until_call",
}}
wait_time
动作描述：
沉默等待时间，等待一段时间后回复
{{
"action": "wait_time",
"time":"等待时间",
}}
{action_options_text}
请选择合适的action，并说明触发action的消息id和选择该action的原因。消息id格式:m+数字
先输出你的选择思考理由，再输出你选择的action，理由是一段平文本，不要分点，精简。
**动作选择要求**
请你根据聊天内容和用户的最新消息选择合适的动作:
1.思考**所有**的可用的action中的**每个动作**是否符合当下条件，如果动作使用调节符合当下条件就使用
2.如果相同的内容已经被执行，请不要重复执行
3.你的兴趣是：{interest}
4.请控制你的发言频率，不要太过频繁的发言
5.如果有人对你感到厌烦，请减少回复
6.如果有人对你进行攻击，或者情绪激动，请你以合适的方法应对
请你根据聊天内容,用户的最新消息和以下标准选择合适的动作:
{plan_style}
{moderation_prompt}
请选择所有符合使用要求的action，动作用json格式输出，如果输出多个json，每个json都要单独用```json包裹，你可以重复使用同一个动作或不同动作:
@@ -175,7 +165,7 @@ class ActionPlanner:
try:
action = action_json.get("action", "no_action")
reasoning = action_json.get("reason", "未提供原因")
action_data = {key: value for key, value in action_json.items() if key not in ["action", "reasoning"]}
action_data = {key: value for key, value in action_json.items() if key not in ["action", "reason"]}
# 非no_action动作需要target_message_id
target_message = None
@@ -357,6 +347,7 @@ class ActionPlanner:
moderation_prompt=moderation_prompt_block,
name_block=name_block,
interest=interest,
plan_style=global_config.personality.plan_style,
)
return prompt, message_id_list

8
src/chat/utils/utils_image.py
View File

@@ -153,7 +153,7 @@ class ImageManager:
"这是一个表情包，请详细描述一下表情包所表达的情感和内容，描述细节，从互联网梗,meme的角度去分析"
)
detailed_description, _ = await self.vlm.generate_response_for_image(
vlm_prompt, image_base64, image_format, temperature=0.4, max_tokens=300
vlm_prompt, image_base64, image_format, temperature=0.4
)
if detailed_description is None:
@@ -175,7 +175,7 @@ class ImageManager:
# 使用较低温度确保输出稳定
emotion_llm = LLMRequest(model_set=model_config.model_task_config.utils, request_type="emoji")
emotion_result, _ = await emotion_llm.generate_response_async(
emotion_prompt, temperature=0.3, max_tokens=50
emotion_prompt, temperature=0.3
)
if not emotion_result:
@@ -270,7 +270,7 @@ class ImageManager:
# 调用AI获取描述
image_format = Image.open(io.BytesIO(image_bytes)).format.lower() # type: ignore
prompt = global_config.custom_prompt.image_prompt
prompt = global_config.personality.visual_style
logger.info(f"[VLM调用] 为图片生成新描述 (Hash: {image_hash[:8]}...)")
description, _ = await self.vlm.generate_response_for_image(
prompt, image_base64, image_format, temperature=0.4, max_tokens=300
@@ -566,7 +566,7 @@ class ImageManager:
image_format = Image.open(io.BytesIO(image_bytes)).format.lower() # type: ignore
# 构建prompt
prompt = global_config.custom_prompt.image_prompt
prompt = global_config.personality.visual_style
# 获取VLM描述
description, _ = await self.vlm.generate_response_for_image(